❓ Question 1:
What is the difference between a population and a sample in statistics?
1. A population is a subset of a sample.
2. A sample is a subset of a population.
3. A population is a larger group, while a sample is a smaller group.
4. A sample is a group that is more representative than a population.
✅ Correct Response: 2
Explanation: In statistics, a population is the entire group of individuals, objects, or events that we are interested in studying, while a sample is a smaller subset of the population that is selected for study. Samples are often used when it is not feasible or practical to study the entire population
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What is the difference between a population and a sample in statistics?
1. A population is a subset of a sample.
2. A sample is a subset of a population.
3. A population is a larger group, while a sample is a smaller group.
4. A sample is a group that is more representative than a population.
✅ Correct Response:
Explanation: In statistics, a population is the entire group of individuals, objects, or events that we are interested in studying, while a sample is a smaller subset of the population that is selected for study. Samples are often used when it is not feasible or practical to study the entire population
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👍10
What is a z-score?
1. A standardized value that indicates the number of standard deviations an observation is from the mean.
2. The range between the highest and lowest values in a set of data.
3. A measure of the spread of a set of data.
4. A measure of central tendency of a set of data.
Explanation: In statistics, a z-score is a standardized value that indicates the number of standard deviations an observation is from the mean of a set of datIt is used to compare values from different normal distributions and to calculate probabilities.
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👍10
The function ____ is used to load a CSV file into a DataFrame in Pandas.
Option 1: read_csv()
Option 2: to_csv()
Option 3: read_excel()
Option 4: load_csv()
Explanation: The read_csv() function is used to load a CSV file into a DataFrame in Pandas. It provides many parameters to read CSV data in a flexible way.
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👍7
When creating a DataFrame in Pandas, which data structures can be used as input?
Option 1: Dictionaries
Option 2: NumPy ndarrays
Option 3: Series
Option 4: Python Lists
Explanation: When creating a DataFrame in Pandas, various data structures can be used as input. These include Dictionaries, NumPy ndarrays, Pandas Series, and Python Lists. Each of these can be converted into a DataFrame, which then allows for flexible data manipulations in the form of a structured grid.
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👍11
The NumPy library is often used for performing ____ operations on large arrays and matrices.
Option 1: Mathematical
Option 2: Statistical
Option 3: Linear algebra
Option 4: All of the above
Explanation: The NumPy library is often used for performing mathematical, statistical, and linear algebra operations on large arrays and matrices. It provides efficient functions and operations to manipulate and analyze numerical data. NumPy is widely used in scientific computing and data analysis tasks
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👍9❤1